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DOCK 6:新特性及当前对接性能的影响

DOCK 6: Impact of new features and current docking performance.

作者信息

Allen William J, Balius Trent E, Mukherjee Sudipto, Brozell Scott R, Moustakas Demetri T, Lang P Therese, Case David A, Kuntz Irwin D, Rizzo Robert C

机构信息

Department of Applied Mathematics & Statistics, Stony Brook University, Stony Brook, New York, 11794.

出版信息

J Comput Chem. 2015 Jun 5;36(15):1132-56. doi: 10.1002/jcc.23905.

Abstract

This manuscript presents the latest algorithmic and methodological developments to the structure-based design program DOCK 6.7 focused on an updated internal energy function, new anchor selection control, enhanced minimization options, a footprint similarity scoring function, a symmetry-corrected root-mean-square deviation algorithm, a database filter, and docking forensic tools. An important strategy during development involved use of three orthogonal metrics for assessment and validation: pose reproduction over a large database of 1043 protein-ligand complexes (SB2012 test set), cross-docking to 24 drug-target protein families, and database enrichment using large active and decoy datasets (Directory of Useful Decoys [DUD]-E test set) for five important proteins including HIV protease and IGF-1R. Relative to earlier versions, a key outcome of the work is a significant increase in pose reproduction success in going from DOCK 4.0.2 (51.4%) → 5.4 (65.2%) → 6.7 (73.3%) as a result of significant decreases in failure arising from both sampling 24.1% → 13.6% → 9.1% and scoring 24.4% → 21.1% → 17.5%. Companion cross-docking and enrichment studies with the new version highlight other strengths and remaining areas for improvement, especially for systems containing metal ions. The source code for DOCK 6.7 is available for download and free for academic users at http://dock.compbio.ucsf.edu/.

摘要

本手稿介绍了基于结构的设计程序DOCK 6.7的最新算法和方法进展,重点包括更新的内部能量函数、新的锚点选择控制、增强的最小化选项、足迹相似性评分函数、对称校正的均方根偏差算法、数据库过滤器和对接取证工具。开发过程中的一项重要策略是使用三个正交指标进行评估和验证:在包含1043个蛋白质-配体复合物的大型数据库(SB2012测试集)上进行构象重现、交叉对接至24个药物-靶点蛋白家族,以及使用大型活性和诱饵数据集(有用诱饵目录[DUD]-E测试集)对包括HIV蛋白酶和IGF-1R在内的五种重要蛋白质进行数据库富集。相对于早期版本,这项工作的一个关键成果是,由于采样失败率从24.1%降至13.6%再降至9.1%,评分失败率从24.4%降至21.1%再降至17.5%,构象重现成功率从DOCK 4.0.2(5

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4e33/4469538/e8b95b1aab89/nihms678299f1.jpg

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